SQL interview practice becomes much more useful when you treat it as a reasoning exercise instead of a question-collection exercise.
Start with a realistic schema
Use customers, orders, products, events or subscriptions. Ask AI to give you the schema and business context, then solve the question yourself.
Use hints instead of answers
If you get stuck, request one hint. Then try again. Asking for the finished query immediately gives you the answer but removes the practice.
Practice the failure modes interviewers actually expose
- duplicate rows
- NULL values
- many-to-many joins
- wrong date boundaries
- incorrect aggregation level
- ambiguous metric definitions
Make the problem harder
After solving the first version, ask AI to add a second condition, change the time window, introduce a data-quality problem or require a performance-conscious approach.
Review the query like an interviewer
Ask AI to identify unnecessary joins, hidden assumptions, aggregation risks and edge cases. Then explain your own query aloud without reading it.
Measure progress properly
Track time to first correct approach, number of hints required and recurring error types. “I solved 50 questions” is less useful than knowing your joins fail under pressure.
For a broader interview system, see the SQL interview question guide.